6897

Efficient Model-based 3D Tracking of Hand Articulations using Kinect

Iason Oikonomidis, Nikolaos Kyriazis, Antonis A. Argyros
Computational Vision and Robotics Lab., Institute of Computer Science, FORTH
22nd British Machine Vision Conference (BMVC’2011), 2011

@article{oikonomidis2011efficient,

   title={Efficient model-based 3d tracking of hand articulations using kinect},

   author={Oikonomidis, I. and Kyriazis, N. and Argyros, A.},

   journal={Procs. of BMVC, Dundee, UK (August 29–September 10 2011)[547]},

   year={2011}

}

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We present a novel solution to the problem of recovering and tracking the 3D position, orientation and full articulation of a human hand from markerless visual observations obtained by a Kinect sensor. We treat this as an optimization problem, seeking for the hand model parameters that minimize the discrepancy between the appearance and 3D structure of hypothesized instances of a hand model and actual hand observations. This optimization problem is effectively solved using a variant of Particle Swarm Optimization (PSO). The proposed method does not require special markers and/or a complex image acquisition setup. Being model based, it provides continuous solutions to the problem of tracking hand articulations. Extensive experiments with a prototype GPU-based implementation of the proposed method demonstrate that accurate and robust 3D tracking of hand articulations can be achieved in near real-time (15Hz).
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